Hero gauges + 'next round hour' semantics

- src/weather_ui.py: new hero_gauges() returns three side-by-side
Plotly Indicator gauges — Ecowitt now (black), Toto next hour
(blue), NWS next hour (red). Forecast gauges show a delta vs the
current reading. Background bands tint cool/warm so the eye can
read the temperature regime without checking the axis.
- src/weather_ui.py: hero_markdown target switches from now+1h to
now.ceil('h'). At 3:55 the hero forecast is for 4 PM; at 4:01 it
flips to 5 PM. Row labels read '(next hour)' instead of '(1 h-ahead)'.
- app.py: build the gauge figure each refresh from realtime + the
nearest Toto/NWS values to the next round hour. Render the gauge
trio directly above the hero table.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app.py

@@ -22,6 +22,7 @@ from src.forecast import forecast_series
 from src.weather_ui import (
     aligned_comparison_markdown,
     combined_figure,
+    hero_gauges,
     hero_markdown,
     residual_figure,
 )
@@ -274,6 +275,30 @@ def refresh():
         nws_temp=week["nws_aligned"].get("temp_f"),
         horizon_hours=1,
     )
+
+    # Gauge trio above the hero table: current Ecowitt + each model's
+    # next-round-hour prediction.
+    cur_temp_for_gauge = (
+        float(realtime["temp_f"]) if realtime and realtime.get("temp_f") is not None
+        else float("nan")
+    )
+    next_hour_utc = pd.Timestamp.now(tz="UTC").ceil("h")
+
+    def _nearest_value(series, target):
+        if series is None or series.empty:
+            return None
+        idx = series.index.get_indexer([target], method="nearest")[0]
+        if idx < 0 or idx >= len(series):
+            return None
+        return float(series.iloc[idx])
+
+    toto_temp_fcst = week["totos"].get("temp_f")
+    toto_next = _nearest_value(
+        toto_temp_fcst.median if toto_temp_fcst is not None else None,
+        next_hour_utc,
+    )
+    nws_next = _nearest_value(week["nws_aligned"].get("temp_f"), next_hour_utc)
+    gauge_fig = hero_gauges(cur_temp_for_gauge, toto_next, nws_next)
     if "temp_f" in week["totos"]:
         comparison_md = (
             "### 🆚 Toto vs NWS — same hour, side-by-side\n\n"
@@ -293,7 +318,7 @@ def refresh():
     resid_fig = residual_figure(resid_df) if not resid_df.empty else None
 
     persist.push_db_async()
-    return hero, comparison_md, week["fig"], scoreboard, resid_fig
+    return hero, gauge_fig, comparison_md, week["fig"], scoreboard, resid_fig
 
 
 # --- scoreboard ----------------------------------------------------------
@@ -435,6 +460,7 @@ with gr.Blocks(title="Toto Weather Forecast", theme=gr.themes.Soft()) as demo:
     gr.Markdown(SUBTITLE)
 
     hero_md = gr.Markdown()
+    gauge_plot = gr.Plot(label="Now vs next-hour forecasts", show_label=False)
     gr.Markdown(f"### 📅 {VIEW_WEEK['label']}")
     week_plot = gr.Plot(label="Weekly")
     comparison_md = gr.Markdown()
@@ -504,7 +530,7 @@ with gr.Blocks(title="Toto Weather Forecast", theme=gr.themes.Soft()) as demo:
             "Full spec: [`docs/toto-inference.md`](https://huggingface.co/spaces/bitsofchris/time-series-ai-weather-forecast/blob/main/docs/toto-inference.md)."
         )
 
-    outputs = [hero_md, comparison_md, week_plot, scoreboard_md, residual_plot]
+    outputs = [hero_md, gauge_plot, comparison_md, week_plot, scoreboard_md, residual_plot]
     demo.load(refresh, outputs=outputs)
 
 

src/weather_ui.py

@@ -93,7 +93,9 @@ def hero_markdown(
         if isinstance(row, pd.Series) and "short_forecast" in row:
             glyph = emoji_for(str(row["short_forecast"]))
 
-    target = pd.Timestamp.now(tz="UTC") + pd.Timedelta(hours=horizon_hours)
+    # 'Next round hour' — if it's 3:55, target = 4 PM. If it's 4:01,
+    # target = 5 PM. Matches what people intuit by 'in the next hour'.
+    target = pd.Timestamp.now(tz="UTC").ceil("h")
 
     def _nearest(series, target_ts):
         if series is None or series.empty:
@@ -115,8 +117,8 @@ def hero_markdown(
         "| Source | Temperature | When |\n"
         "|---|---|---|\n"
         f"| 📡 Ecowitt (now) | **{cur_temp:.1f}°F** | {eco_when} |\n"
-        f"{_row(f'🤖 Toto ({horizon_hours} h-ahead)', toto_val, toto_idx)}\n"
-        f"{_row(f'🌎 NWS ({horizon_hours} h-ahead)', nws_val, nws_idx)}"
+        f"{_row('🤖 Toto (next hour)', toto_val, toto_idx)}\n"
+        f"{_row('🌎 NWS (next hour)', nws_val, nws_idx)}"
     )
     return f"### {glyph} {place}\n\n{table}"
 
@@ -178,6 +180,57 @@ def emoji_strip_markdown(nws_df: pd.DataFrame, tz: str, n: int = 12) -> str:
     return f"| {hours} |\n{sep}\n| {glyphs} |\n| {temps} |"
 
 
+def hero_gauges(
+    cur_temp: float,
+    toto_next: float | None,
+    nws_next: float | None,
+    temp_range: tuple[float, float] = (20.0, 100.0),
+) -> go.Figure:
+    """Three side-by-side gauges: current Ecowitt temperature, plus each
+    model's prediction for the next round hour. Each forecast gauge also
+    shows its delta vs the current reading."""
+    cool_to_warm = [
+        {"range": [20, 40], "color": "rgba(31,119,180,0.18)"},
+        {"range": [40, 60], "color": "rgba(31,119,180,0.08)"},
+        {"range": [60, 80], "color": "rgba(214,39,40,0.08)"},
+        {"range": [80, 100], "color": "rgba(214,39,40,0.18)"},
+    ]
+    specs = [[{"type": "indicator"}, {"type": "indicator"}, {"type": "indicator"}]]
+    fig = make_subplots(rows=1, cols=3, specs=specs)
+
+    def _ind(value, title, bar_color, with_delta: bool):
+        ind = go.Indicator(
+            mode="gauge+number+delta" if with_delta else "gauge+number",
+            value=value if value is not None else float("nan"),
+            title={"text": title, "font": {"size": 14}},
+            number={"suffix": " °F", "font": {"size": 30}},
+            gauge=dict(
+                axis=dict(range=list(temp_range), tickwidth=1, tickcolor="#888"),
+                bar=dict(color=bar_color, thickness=0.25),
+                bgcolor="white",
+                borderwidth=1,
+                bordercolor="#e0e0e0",
+                steps=cool_to_warm,
+                threshold=dict(line=dict(color=bar_color, width=4), value=value or 0),
+            ),
+            delta=(
+                dict(reference=cur_temp, suffix=" °F", increasing={"color": "#d62728"}, decreasing={"color": "#1f77b4"})
+                if with_delta else None
+            ),
+        )
+        return ind
+
+    fig.add_trace(_ind(cur_temp, "📡 Ecowitt (now)", "#222", False), row=1, col=1)
+    fig.add_trace(_ind(toto_next, "🤖 Toto (next hour)", "#1f77b4", True), row=1, col=2)
+    fig.add_trace(_ind(nws_next, "🌎 NWS (next hour)", "#d62728", True), row=1, col=3)
+    fig.update_layout(
+        height=260,
+        margin=dict(l=10, r=10, t=50, b=10),
+        paper_bgcolor="rgba(0,0,0,0)",
+    )
+    return fig
+
+
 def residual_figure(
     df: pd.DataFrame,
     title: str = "Forecast residual — 1 h-ahead prediction minus Ecowitt actual, last 48 h (°F)",